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Error Entropy and Mean Square Error Minimization for Lossless Image Compression
2006 International Conference on Image Processing, 2006In this paper, the minimum error entropy (MEE) criterion is considered as an alternative to the mean square error (MSE) criterion in obtaining predictor coefficients for lossless still image coding. Estimation of the error entropy is done using Renyi's formula.
Peter E. William, Michael W. Hoffman
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Best linear estimation via minimization of relative mean squared error
Statistics and Computing, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lin Su, Howard D. Bondell
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Mean square error minimization in a nonstationary system
IEEE Transactions on Automatic Control, 1965This paper gives a method for the analysis and synthesis of a controller to track a time-varying optimum operating point. In particular, the maximization of the average of a quadratic performance index of a general system is considered where not only the location of the maximum is time-varying, but also the shape of the performance index function.
A. Lavi, E. Mastascusa
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Mean square error minimization using interpolative block truncation coding algorithms
2010 2nd International Conference on Education Technology and Computer, 2010Block Truncation Coding (BTC) is one of spatial coding techniques of images. This technique has a simple and fast algorithm which achieves constant bit rate of 2 bits per pixel. The compression ratio may be improved by coding only half of the bits in the BTC bit plane of each block; the other half will be interpolated at the receiver. The resulting bit
Elghanai. M. Rhoma +1 more
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Nonlinear One-bit Precoding for Massive MIMO Downlink: Minimizing the Maximum Mean Squared Error
2021 IEEE Wireless Communications and Networking Conference (WCNC), 2021In this paper, we study the nonlinear one-bit pre-coding in the massive multiple-input multiple-output downlink system. Different from the conventional criterion of minimizing the sum of mean squared error (min-sum MSE) of all users, the criterion of minimizing the maximum MSE (min-max MSE) is considered here which is more suitable for communications ...
Xingyu Yuan, Jianping Zheng
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Optimal Information Criteria Minimizing Their Asymptotic Mean Square Errors
Sankhya B, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Uniqueness characteristics of the 2-D IIR mean squared error minimization
Proceedings of 1st International Conference on Image Processing, 2002Several different two-dimensional adaptive filter structures and algorithms have been developed, the most recent of which is a 2D IIR adaptive filter. Two-dimensional IIR adaptive filters can be used in a variety of image and video processing applications.
J.C. Strait, W.K. Jenkins
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Algorithm for sparse representation minimizing mean square error of power spectrograms
2015 IEEE International Conference on Digital Signal Processing (DSP), 2015Sparse representation is an idea to approximate a target signal by a linear combination of a small number of sample signals, and it is utilized in various research fields. In this paper, we evaluate the approximation error of signals by the mean square error of power spectrograms (P-MSE).
Yuma Tanaka +2 more
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Bias Adjustment Minimizing the Asymptotic Mean Square Error
Communications in Statistics - Theory and Methods, 2013A method of bias adjustment which minimizes the asymptotic mean square error is presented for an estimator typically given by maximum likelihood. Generally, this adjustment includes unknown population values. However, in some examples, the adjustment can be done without population values.
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Supermodular mean squared error minimization for sensor scheduling in optimal Kalman Filtering
2017 American Control Conference (ACC), 2017We consider the problem of scheduling a set of sensors to observe the state of a discrete-time linear system subject to a limited energy budget. Our goal is to devise a sensor schedule that minimizes the mean squared error (MSE) of an optimal estimator (i.e., the Kalman Filter). Both the minimum-MSE and the minimum-cardinality optimal sensor scheduling
Prince Singh +5 more
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